Crosstalk between non-coding RNAs expression profile, drug resistance and immune response in breast cancer

Miraghel, Seyed Ali; Ebrahimi, Nader; Khani, Leila; Mansouri, Atena; Jafarzadeh, Asieh; Ahmadi, Amirhossein; Aref, Amir Reza

doi:10.1016/j.phrs.2021.106041

Cited by 19 publications

(8 citation statements)

References 158 publications

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“…However, preclinical studies have shown that UPR promotes tumor progression by affecting processes, including metabolism, angiogenesis, chemoresistance, and metastasis. For instance, the homeostatic target of IRE1α XBP1 promoted tumor development in various preclinical animal models of triple‐negative breast cancer (TNBC; X. Chen et al, 2014; Miraghel et al, 2022). IRE1α deletion in a human glioma cell line hindered angiogenesis and inhibited tumor development when these cells were implanted into mice (Bobrovnikova‐Marjon et al, 2010; Feng et al, 2014; Sheng et al, 2019).…”

Section: Effects Of Er Stress On Tumor Progression Via the Upr Pathwaymentioning

confidence: 99%

The role of endoplasmic reticulum stress in the regulation of long noncoding RNAs in cancer

Ebrahimi

Saremi

Ghanaatian

et al. 2022

Journal Cellular Physiology

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Cancer cells must overcome a variety of external and internal stresses to survive and proliferate. These unfavorable conditions include the accumulation of mutations, nutrient deficiency, oxidative stress, and hypoxia. These stresses can cause aggregation of misfolded proteins inside the endoplasmic reticulum. Under these conditions, the cell undergoes endoplasmic reticulum stress (ER‐stress), and consequently initiates the unfolded protein response (UPR). Activation of the UPR triggers transcription factors and regulatory factors, including long noncoding RNAs (lncRNAs), which control the gene expression profile to maintain cellular stability and hemostasis. Recent investigations have shown that cancer cells can ensure their survival under adverse conditions by the UPR affecting the expression of lncRNAs. Therefore, understanding the relationship between lncRNA expression and ER stress could open new avenues, and suggest potential therapies to treat various types of cancer.

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Section: Effects Of Er Stress On Tumor Progression Via the Upr Pathwaymentioning

confidence: 99%

The role of endoplasmic reticulum stress in the regulation of long noncoding RNAs in cancer

Ebrahimi

Saremi

Ghanaatian

et al. 2022

Journal Cellular Physiology

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“…Breast cancer (BC), the most prevalent malignant tumor globally, is characterized by significant heterogeneity 1 . It poses a considerable health risk to women 2–4 . Despite advances in early detection and treatment, drug resistance remains a primary obstacle, often leading to poor prognosis in various malignancies.…”

Section: Introductionmentioning

confidence: 99%

“…1 It poses a considerable health risk to women. [2][3][4] Despite advances in early detection and treatment, drug resistance remains a primary obstacle, often leading to poor prognosis in various malignancies. The treatment methods for BC extend from surgical intervention to chemotherapy, radiotherapy, endocrine therapy, anti-HER2 therapy and immunotherapy.…”

Section: Introductionmentioning

confidence: 99%

Development of a novel prognostic signature based on single‐cell combined bulk RNA analysis in breast cancer

Xiao,

Hu,

Xie

et al. 2024

The Journal of Gene Medicine

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BackgroundBreast cancer (BC), a malignant tumor, is a significant cause of death and disability among women globally. Recent research indicates that copy number variation plays a crucial role in tumor development. In this study, we employed the Single‐Cell Variational Aneuploidy Analysis (SCEVAN) algorithm to differentiate between malignant and non‐malignant cells, aiming to identify genetic signatures with prognostic relevance for predicting patient survival.MethodsWe analyzed gene expression profiles and associated clinical data from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Using the SCEVAN algorithm, we distinguished malignant from non‐malignant cells and investigated cellular interactions within the tumor microenvironment (TME). We categorized TCGA samples based on differentially expressed genes (DEGs) between these cell types. Subsequent Kyoto Encyclopedia of Genes and Genomes pathway analysis was conducted. Additionally, we developed polygenic models for the DEGs using least absolute shrinkage and selection operator‐penalized Cox regression analysis. To assess the prognostic accuracy of these characteristics, we generated Kaplan–Meier and receiver operating characteristic curves from training and validation datasets. We also monitored the expression variations of prognostic genes across the pseudotime of malignant cells. Patients were divided into high‐risk and low‐risk groups based on median risk scores to compare their TME and identify potential therapeutic agents. Lastly, polymerase chain reaction was used to validate seven pivotal genes.ResultsThe SCEVAN algorithm identified distinct malignant and non‐malignant cells in GSE180286. Cellchat analysis revealed significantly increased cellular communication, particularly between fibroblasts, endothelial cells and malignant cells. The DEGs were predominantly involved in immune‐related pathways. TCGA samples were classified into clusters A and B based on these genes. Cluster A, enriched in immune pathways, was associated with poorer prognosis, whereas cluster B, predominantly involved in circadian rhythm pathways, showed better outcomes. We constructed a 14‐gene prognostic signature, validated in a 1:1 internal TCGA cohort and external GEO datasets (GSE42568 and GSE146558). Kaplan–Meier analysis confirmed the prognostic signature's accuracy (p < 0.001). Receiver operating characteristic curve analysis demonstrated the predictive reliability of these prognostic features. Single‐cell pseudotime analysis with monocle2 highlighted the distinct expression trends of these genes in malignant cells, underscoring the intratumoral heterogeneity. Furthermore, we explored the differences in TME between high‐ and low‐risk groups and identified 16 significantly correlated drugs.ConclusionOur findings suggest that the 14‐gene prognostic signature could serve as a novel biomarker for forecasting the prognosis of BC patients. Additionally, the immune cells and pathways in different risk groups indicate that immunotherapy may be a crucial component of treatment strategies for BC patients.

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“…The evasion of immune surveillance, tumor cell invasion and resistance to therapy are linked to substance and energy metabolism, with amino acid metabolism being a vital component in the growth and survival of breast cancer cells. 2,3 Amino acids play a crucial role not only in protein synthesis but also in serving as precursors for nucleotide synthesis and energy metabolism. Dysregulated cellular energetics, including disrupted amino acid metabolism, is a hallmark of cancer, which can facilitate tumor growth and metastasis.…”

Section: Introductionmentioning

confidence: 99%

“…As breast cancer is a highly proliferative condition, it necessitates a continuous supply of nutrients to satisfy its metabolic requirements. The evasion of immune surveillance, tumor cell invasion and resistance to therapy are linked to substance and energy metabolism, with amino acid metabolism being a vital component in the growth and survival of breast cancer cells 2,3 . Amino acids play a crucial role not only in protein synthesis but also in serving as precursors for nucleotide synthesis and energy metabolism.…”

Section: Introductionmentioning

confidence: 99%

Amino acids and their roles in tumor immunotherapy of breast cancer

Xia,

Zhu,

Zheng

et al. 2023

The Journal of Gene Medicine

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Breast cancer is the most commonly diagnosed cancer among women. The primary treatment options include surgery, radiotherapy, chemotherapy, targeted therapy and hormone therapy. The effectiveness of breast cancer therapy varies depending on the stage and aggressiveness of the cancer, as well as individual factors. Advances in early detection and improved treatments have significantly increased survival rates for breast cancer patients. Nevertheless, specific subtypes of breast cancer, particularly triple‐negative breast cancer, still lack effective treatment strategies. Thus, novel and effective therapeutic targets for breast cancer need to be explored. As substrates of protein synthesis, amino acids are important sources of energy and nutrition, only secondly to glucose. The rich supply of amino acids enables the tumor to maintain its proliferative competence through participation in energy generation, nucleoside synthesis and maintenance of cellular redox balance. Amino acids also play an important role in immune‐suppressive microenvironment formation. Thus, the biological effects of amino acids may change unexpectedly in tumor‐specific or oncogene‐dependent manners. In recent years, there has been significant progress in the study of amino acid metabolism, particularly in their potential application as therapeutic targets in breast cancer. In this review, we provide an update on amino acid metabolism and discuss the therapeutic implications of amino acids in breast cancer.

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Crosstalk between non-coding RNAs expression profile, drug resistance and immune response in breast cancer

Cited by 19 publications

References 158 publications

The role of endoplasmic reticulum stress in the regulation of long noncoding RNAs in cancer

The role of endoplasmic reticulum stress in the regulation of long noncoding RNAs in cancer

Development of a novel prognostic signature based on single‐cell combined bulk RNA analysis in breast cancer

Amino acids and their roles in tumor immunotherapy of breast cancer

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